Sleep apnoea increases biomarkers of immune evasion, lymphangiogenesis and tumour cell aggressiveness in high-risk patients and those with established lung cancer.

Background: Intermittent hypoxaemia and obstructive sleep apnoea (OSA) have been linked to lung cancer through as yet unidentified pathophysiological mechanisms. This study evaluates the effect of OSA on serum levels of biomarkers of immunosurveillance, lymphangiogenesis and intrinsic tumour cell aggressiveness in high-risk individuals screened for lung cancer and patients with established lung cancer. Methods: Serum samples from individuals participating in a lung cancer screening cohort (SAILS study) or with newly diagnosed lung cancer (SAIL study) were analysed. All patients underwent home sleep apnoea testing. Soluble levels of programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), cytotoxic T-lymphocyte antigen-4, midkine (MDK), paraspeckle component-1 (PSPC1), transforming growth factor-ß1 (TGF-ß1), SMAD3, matrix metalloproteinase-2 and co-stimulus receptor of the tumour necrosis factor family of receptors (CD137) were determined by ELISA. Results: The presence of moderate-to-severe OSA was associated with increased levels of PSPC1, MDK, PD-L1 and PD-1 in screened individuals, and with higher values of PSPC1, TGF-ß1, PD-L1 and PD-1 in patients with established lung cancer. The findings correlated with nocturnal intermittent hypoxaemia indices. Conclusion: Moderate-to-severe OSA is associated with increased expression of serum biomarkers of immune evasion, lymphangiogenesis and tumour cell aggressiveness in high-risk individuals screened for lung cancer and those with established disease.

Untargeted Metabolomic Study of Lung Cancer Patients after Surgery with Curative Intent.

Lung cancer (LC) is a leading cause of mortality, claiming more than 1.8 million deaths per year worldwide. Surgery is one of the most effective treatments when the disease is in its early stages. The study of metabolic alterations after surgical intervention with curative intent could be used to assess the response to treatment or the detection of cancer recurrence. In this study, we have evaluated the metabolomic profile of serum samples (n = 110) from preoperative (PRE) and postoperative (POST) LC patients collected at two different time points (1 month, A; 3-6 months, B) with respect to healthy people. An untargeted metabolomic platform based on reversed phase (RP) and hydrophilic interaction chromatography (HILIC), using ultra-high performance liquid chromatography (UHPLC) and mass spectrometry (MS), was applied (MassIVE ID MSV000092213). Twenty-two altered metabolites were annotated by comparing all the different studied groups. DG(14,0/22:1), stearamide, proline, and E,e-carotene-3,3'-dione were found altered in PRE, and their levels returned to those of a baseline control group 3-6 months after surgery. Furthermore, 3-galactosyllactose levels remained altered after intervention in some patients. This study provides unique insights into the metabolic profiles of LC patients after surgery at two different time points by combining complementary analytical methods.

European Respiratory Society short guidelines for the use of as-needed ICS/formoterol in mild asthma.

Recent clinical trials of as-needed fixed-dose combination of inhaled corticosteroid (ICS)/formoterol have provided new evidence that may warrant a reconsideration of current practice. A Task Force was set up by the European Respiratory Society to provide evidence-based recommendations on the use of as-needed ICS/formoterol as treatment for mild asthma. The Task Force defined two questions that were assessed using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach. The Task Force utilised the outcomes to develop recommendations for a pragmatic guideline for everyday clinical practice. The Task Force suggests that adults with mild asthma use as-needed ICS/formoterol instead of regular ICS maintenance treatment plus as-needed short-acting ß2-antagonist (SABA) and that adolescents with mild asthma use either as-needed ICS/formoterol or ICS maintenance treatment plus as-needed SABA (conditional recommendation; low certainty of evidence). The recommendation for adults places a relatively higher value on the reduction of systemic corticosteroid use and the outcomes related to exacerbations, and a relatively lower value on the small differences in asthma control. Either treatment option is suggested for adolescent patients as the balance is very close and data more limited. The Task Force recommends that adult and adolescent patients with mild asthma use as-needed ICS/formoterol instead of as-needed SABA (strong recommendation; low certainty of evidence). This recommendation is based on the benefit of as-needed ICS/formoterol in mild asthma on several outcomes and the risks related to as-needed SABA in the absence of anti-inflammatory treatment. The implementation of this recommendation is hampered in countries (including European Union countries) where as-needed ICS/formoterol is not approved for mild asthma.

Metallomic Signatures of Lung Cancer and Chronic Obstructive Pulmonary Disease.

Lung cancer (LC) is the leading cause of cancer deaths, and chronic obstructive pulmonary disease (COPD) can increase LC risk. Metallomics may provide insights into both of these tobacco-related diseases and their shared etiology. We conducted an observational study of 191 human serum samples, including those of healthy controls, LC patients, COPD patients, and patients with both COPD and LC. We found 18 elements (V, Al, As, Mn, Co, Cu, Zn, Cd, Se, W, Mo, Sb, Pb, Tl, Cr, Mg, Ni, and U) in these samples. In addition, we evaluated the elemental profiles of COPD cases of varying severity. The ratios and associations between the elements were also studied as possible signatures of the diseases. COPD severity and LC have a significant impact on the elemental composition of human serum. The severity of COPD was found to reduce the serum concentrations of As, Cd, and Tl and increased the serum concentrations of Mn and Sb compared with healthy control samples, while LC was found to increase Al, As, Mn, and Pb concentrations. This study provides new insights into the effects of LC and COPD on the human serum elemental profile that will pave the way for the potential use of elements as biomarkers for diagnosis and prognosis. It also sheds light on the potential link between the two diseases, i.e., the evolution of COPD to LC.

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performance with respect to human reader severity assessment and whole lung radiomics. We propose a deep learning based scheme to automatically segment the different lesion subtypes in nonenhanced CT scans. The automatic lesion quantification was used to predict clinical outcomes. The proposed technique has been independently tested in a multicentric cohort of 103 patients, retrospectively collected between March and July of 2020. Segmentation of lesion subtypes was evaluated using both overlapping (Dice) and distance-based (Hausdorff and average surface) metrics, while the proposed system to predict clinically relevant outcomes was assessed using the area under the curve (AUC). Additionally, other metrics including sensitivity, specificity, positive predictive value and negative predictive value were estimated. 95% confidence intervals were properly calculated. The agreement between the automatic estimate of parenchymal damage (%) and the radiologists' severity scoring was strong, with a Spearman correlation coefficient (R) of 0.83. The automatic quantification of lesion subtypes was able to predict patient mortality, admission to the Intensive Care Units (ICU) and need for mechanical ventilation with an AUC of 0.87, 0.73 and 0.68 respectively. The proposed artificial intelligence system enabled a better prediction of those clinically relevant outcomes when compared to the radiologists' interpretation and to whole lung radiomics. In conclusion, deep learning lesion subtyping in COVID-19 pneumonia from noncontrast chest CT enables quantitative assessment of disease severity and better prediction of clinical outcomes with respect to whole lung radiomics or radiologists' severity score.

A multicentre, randomized controlled trial of telehealth for the management of COPD.

BACKGROUND: Evidence is needed to determine the role of telehealth (TH) in COPD management. METHODS: PROMETE II was a multicentre, randomized, 12-month trial. Severe COPD patients in stable condition were randomized to a specific monitoring protocol with TH or routine clinical practice (RCP). The primary objective was to reduce the number of COPD exacerbations leading to ER visits/hospital admissions between groups. RESULTS: Overall, 237 COPD patients were screened, and 229 (96.6%) were randomized to TH (n = 115) or RCP (n = 114), with age of 71 ±â€¯8 years and 80% were men. Overall, 169 completed the full follow-up period. There were no statistical differences at one year between groups in the proportion of participants who had a COPD exacerbation (60% in TH vs. 53.5% in RCP; p = 0.321). There was, however, a marked but non-significant trend towards a shorter duration of hospitalization and days in ICU in the TH group (18.9 ±â€¯16.0 and 6.0 ±â€¯4.6 days) compared to the RCP group (22.4 ±â€¯19.5 and 13.3 ±â€¯11.1 days). The number of all-cause deaths was comparable between groups (12 in TH vs. 13 in RCP) as was total resource utilization cost (7912€ in TH vs. 8918€ in RCP). Telehealth was evaluated highly positively by patients and doctors. CONCLUSIONS: Remote patient management did not reduce COPD-related ER visits or hospital admissions compared to RCP within 12 months.